knitr::opts_chunk$set(echo = FALSE,cache = TRUE)
library(xlsx)
library(ggplot2)
## Registered S3 methods overwritten by 'ggplot2':
##   method         from 
##   [.quosures     rlang
##   c.quosures     rlang
##   print.quosures rlang
library(gplots)
## 
## Attaching package: 'gplots'
## The following object is masked from 'package:stats':
## 
##     lowess
library(gridExtra)
library(corrplot)
## corrplot 0.84 loaded
library(dplyr)
## 
## Attaching package: 'dplyr'
## The following object is masked from 'package:gridExtra':
## 
##     combine
## The following objects are masked from 'package:stats':
## 
##     filter, lag
## The following objects are masked from 'package:base':
## 
##     intersect, setdiff, setequal, union
library(png)
library(grid)
library(heatmaply)
## Loading required package: plotly
## 
## Attaching package: 'plotly'
## The following object is masked from 'package:ggplot2':
## 
##     last_plot
## The following object is masked from 'package:stats':
## 
##     filter
## The following object is masked from 'package:graphics':
## 
##     layout
## Loading required package: viridis
## Loading required package: viridisLite
## Registered S3 method overwritten by 'seriation':
##   method         from 
##   reorder.hclust gclus
## 
## ======================
## Welcome to heatmaply version 0.16.0
## 
## Type citation('heatmaply') for how to cite the package.
## Type ?heatmaply for the main documentation.
## 
## The github page is: https://github.com/talgalili/heatmaply/
## Please submit your suggestions and bug-reports at: https://github.com/talgalili/heatmaply/issues
## Or contact: <tal.galili@gmail.com>
## ======================
## Warning: NAs introduced by coercion
##      Tree.ID Allocation Column Row Rep. measure Height Flower Flower.Level
## 840    IN4E4         F1      2  20    N       7      M      N            0
## 1363   IN4FM         F1      3  17    N      11      H      N            0
##         Chl  Flav  Anth Height08 Height09 HD
## 840  18.511 1.401 0.370      138      234 96
## 1363 59.122 1.640 0.483      166      245 79
## Warning: Factor `Height` contains implicit NA, consider using
## `forcats::fct_explicit_na`

Tree Plots

Anthocyanin

## Warning: Removed 21 rows containing non-finite values (stat_boxplot).

## Warning: Removed 21 rows containing missing values (geom_point).

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## Warning: Removed 21 rows containing non-finite values (stat_bin).
## Warning: Removed 21 rows containing non-finite values (stat_density).

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Anth5
##              Df  Sum Sq   Mean Sq F value Pr(>F)
## F1$Tree.ID  158 0.26483 0.0016762  0.9733 0.5779
## Residuals  1631 2.80887 0.0017222

  • R.squared
## [1] 0.08616099

Chlorophyll

## Warning: Removed 21 rows containing non-finite values (stat_boxplot).

## Warning: Removed 21 rows containing missing values (geom_point).

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## Warning: Removed 21 rows containing non-finite values (stat_bin).
## Warning: Removed 21 rows containing non-finite values (stat_density).

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Chl5
##              Df Sum Sq Mean Sq F value Pr(>F)
## F1$Tree.ID  158  23815  150.73  0.6775  0.999
## Residuals  1631 362856  222.47

  • R.squared
## [1] 0.06158903

Flavonol

## Warning: Removed 21 rows containing non-finite values (stat_boxplot).

## Warning: Removed 21 rows containing missing values (geom_point).

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## Warning: Removed 21 rows containing non-finite values (stat_bin).
## Warning: Removed 21 rows containing non-finite values (stat_density).

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Flav5
##              Df Sum Sq  Mean Sq F value    Pr(>F)    
## F1$Tree.ID  158 14.876 0.094149  1.8118 1.856e-08 ***
## Residuals  1631 84.754 0.051965                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared
## [1] 0.149308

Height 2018

## Warning: Removed 89 rows containing non-finite values (stat_boxplot).

## Warning: Removed 8 rows containing missing values (geom_point).

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## Warning: Removed 8 rows containing non-finite values (stat_bin).
## Warning: Removed 8 rows containing non-finite values (stat_density).

  • ANOVA
## Warning in anova.lm(mod181): ANOVA F-tests on an essentially perfect fit
## are unreliable
## Analysis of Variance Table
## 
## Response: F1$H185
##              Df Sum Sq Mean Sq    F value    Pr(>F)    
## F1$Tree.ID  171 418774    2449 3.9594e+27 < 2.2e-16 ***
## Residuals  1550      0       0                         
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Warning: not plotting observations with leverage one:
##   306, 1600, 1609, 1610, 1611, 1614, 1617, 1622, 1630, 1642, 1644, 1653, 1661, 1680, 1681, 1687, 1690, 1698, 1722

## Warning: not plotting observations with leverage one:
##   306, 1600, 1609, 1610, 1611, 1614, 1617, 1622, 1630, 1642, 1644, 1653, 1661, 1680, 1681, 1687, 1690, 1698, 1722

## Warning in sqrt(crit * p * (1 - hh)/hh): NaNs produced
## Warning in sqrt(crit * p * (1 - hh)/hh): NaNs produced

  • R.squared
## [1] 1

Height 2019

## Warning: Removed 90 rows containing non-finite values (stat_boxplot).

## Warning: Removed 9 rows containing missing values (geom_point).

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## Warning: Removed 9 rows containing non-finite values (stat_bin).
## Warning: Removed 9 rows containing non-finite values (stat_density).

  • ANOVA
## Warning in anova.lm(mod191): ANOVA F-tests on an essentially perfect fit
## are unreliable
## Analysis of Variance Table
## 
## Response: F1$H195
##              Df Sum Sq Mean Sq  F value    Pr(>F)    
## F1$Tree.ID  170 429289  2525.2 3.72e+27 < 2.2e-16 ***
## Residuals  1550      0     0.0                       
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Warning: not plotting observations with leverage one:
##   1599, 1610, 1613, 1616, 1620, 1621, 1629, 1641, 1643, 1652, 1660, 1679, 1680, 1686, 1689, 1697, 1721

## Warning: not plotting observations with leverage one:
##   1599, 1610, 1613, 1616, 1620, 1621, 1629, 1641, 1643, 1652, 1660, 1679, 1680, 1686, 1689, 1697, 1721

## Warning in sqrt(crit * p * (1 - hh)/hh): NaNs produced
## Warning in sqrt(crit * p * (1 - hh)/hh): NaNs produced

  • R.squared
## [1] 1

Height Difference 2018-2019

## Warning: Removed 1811 rows containing non-finite values (stat_boxplot).

## Warning: Removed 180 rows containing missing values (geom_point).

## `stat_bin()` using `bins = 30`. Pick better value with `binwidth`.
## Warning: Removed 180 rows containing non-finite values (stat_bin).
## Warning: Removed 180 rows containing non-finite values (stat_density).

  • Anova
## Warning in anova.lm(modHD1): ANOVA F-tests on an essentially perfect fit
## are unreliable
## Analysis of Variance Table
## 
## Response: F1$HD5
##              Df Sum Sq Mean Sq    F value    Pr(>F)    
## F1$Tree.ID  170 382183  2248.1 6.9697e+27 < 2.2e-16 ***
## Residuals  1550      0     0.0                         
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## Warning: not plotting observations with leverage one:
##   1599, 1610, 1613, 1616, 1620, 1621, 1629, 1641, 1643, 1652, 1660, 1679, 1680, 1686, 1689, 1697, 1721

## Warning: not plotting observations with leverage one:
##   1599, 1610, 1613, 1616, 1620, 1621, 1629, 1641, 1643, 1652, 1660, 1679, 1680, 1686, 1689, 1697, 1721

## Warning in sqrt(crit * p * (1 - hh)/hh): NaNs produced
## Warning in sqrt(crit * p * (1 - hh)/hh): NaNs produced

  • R.squared
## [1] 1

Leaf Height Plots

## Warning: Factor `Height` contains implicit NA, consider using
## `forcats::fct_explicit_na`

## Warning: Factor `Height` contains implicit NA, consider using
## `forcats::fct_explicit_na`

## Warning: Factor `Height` contains implicit NA, consider using
## `forcats::fct_explicit_na`

## Warning: Factor `Height` contains implicit NA, consider using
## `forcats::fct_explicit_na`

Anthocyanin

## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).

  • ANOVA Anthocyanin and Collection Height
## Analysis of Variance Table
## 
## Response: F1$Anth5
##             Df Sum Sq   Mean Sq F value Pr(>F)
## F1$Height    2 0.0000 1.650e-06   0.001  0.999
## Residuals 1787 3.0326 1.697e-03

## 
## Call:
## lm(formula = F1$Anth5 ~ F1$Height)
## 
## Residuals:
##       Min        1Q    Median        3Q       Max 
## -0.108092 -0.027610 -0.000777  0.025741  0.198752 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)
## (Intercept) -6.737e-05  1.846e-03  -0.036    0.971
## F1$HeightL   8.195e-05  2.452e-03   0.033    0.973
## F1$HeightM   1.049e-04  2.461e-03   0.043    0.966
## 
## Residual standard error: 0.04119 on 1787 degrees of freedom
##   (21 observations deleted due to missingness)
## Multiple R-squared:  1.089e-06,  Adjusted R-squared:  -0.001118 
## F-statistic: 0.000973 on 2 and 1787 DF,  p-value: 0.999
  • R.squared Collection Height
## [1] 1.08897e-06
  • ANOVA Anthocyanin High vs Mid Heights
## Analysis of Variance Table
## 
## Response: HH$Anth
##            Df   Sum Sq    Mean Sq F value Pr(>F)
## HM$Anth     1 0.000222 0.00022183   0.299 0.5853
## Residuals 157 0.116476 0.00074189

## 
## Call:
## lm(formula = HH$Anth ~ HM$Anth)
## 
## Residuals:
##       Min        1Q    Median        3Q       Max 
## -0.074972 -0.017800 -0.001569  0.019434  0.088874 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)
## (Intercept)  0.0003553  0.0021601   0.164    0.870
## HM$Anth     -0.0594670  0.1087508  -0.547    0.585
## 
## Residual standard error: 0.02724 on 157 degrees of freedom
##   (21 observations deleted due to missingness)
## Multiple R-squared:  0.001901,   Adjusted R-squared:  -0.004456 
## F-statistic: 0.299 on 1 and 157 DF,  p-value: 0.5853
  • R.squared Anthocyanin High vs Mid Heights
## [1] 0.001900911
  • ANOVA Anthocyanin Low vs Mid Heights
## Analysis of Variance Table
## 
## Response: HL$Anth
##            Df   Sum Sq    Mean Sq F value Pr(>F)
## HM$Anth     1 0.000092 0.00009166  0.1926 0.6613
## Residuals 157 0.074704 0.00047582

  • R.squared Anthocyanin Low vs Mid Heights
## [1] 0.001225476
  • ANOVA Anthocyanin High vs Low Heights
## Analysis of Variance Table
## 
## Response: HH$Anth
##            Df   Sum Sq    Mean Sq F value Pr(>F)
## HL$Anth     1 0.000074 0.00007430     0.1 0.7522
## Residuals 157 0.116624 0.00074283

  • R.squared Anthocyanin High vs Low Heights
## [1] 0.000636706

Chlorophyll

## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).

  • ANOVA Chlorophyll and Collection Height
## Analysis of Variance Table
## 
## Response: F1$Chl5
##             Df Sum Sq Mean Sq F value Pr(>F)
## F1$Height    2    802  401.03  1.8488 0.1577
## Residuals 1787 387632  216.92

  • R.squared Collection Height
## [1] 0.002064874
  • ANOVA Chlorophyll High vs Mid Heights
## Analysis of Variance Table
## 
## Response: HH$Chl
##            Df  Sum Sq Mean Sq F value  Pr(>F)  
## HM$Chl      1   439.6  439.57  5.1202 0.02502 *
## Residuals 157 13478.4   85.85                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared Chlorophyll High vs Mid Heights
## [1] 0.03158298
  • ANOVA Chlorophyll Low vs Mid Heights
## Analysis of Variance Table
## 
## Response: HL$Chl
##            Df Sum Sq Mean Sq F value Pr(>F)
## HM$Chl      1  141.6 141.639  2.4422 0.1201
## Residuals 157 9105.6  57.998

  • R.squared Chlorophyll Low vs Mid Heights
## [1] 0.01531687
  • ANOVA Chlorophyll High vs Low Heights
## Analysis of Variance Table
## 
## Response: HH$Chl
##            Df  Sum Sq Mean Sq F value  Pr(>F)  
## HL$Chl      1   526.1  526.06  6.1673 0.01406 *
## Residuals 157 13391.9   85.30                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared Chlorophyll High vs Low Heights
## [1] 0.03779738

Flavonol

## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).

  • ANOVA Flavonol and Collection Height
## Analysis of Variance Table
## 
## Response: F1$Flav5
##             Df Sum Sq  Mean Sq F value Pr(>F)
## F1$Height    2  0.001 0.000562  0.0102 0.9899
## Residuals 1787 98.658 0.055209

  • R.squared Collection Height
## [1] 1.139096e-05
  • ANOVA Flavonol High vs Mid Heights
## Analysis of Variance Table
## 
## Response: HH$Flav
##            Df Sum Sq  Mean Sq F value Pr(>F)  
## HM$Flav     1 0.0540 0.053997  3.1493 0.0779 .
## Residuals 157 2.6919 0.017146                 
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared Flavonol High vs Mid Heights
## [1] 0.01966458
  • ANOVA Flavonol Low vs Mid Heights
## Analysis of Variance Table
## 
## Response: HL$Flav
##            Df Sum Sq  Mean Sq F value  Pr(>F)  
## HM$Flav     1 0.1518 0.151825   5.739 0.01777 *
## Residuals 157 4.1534 0.026455                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared Flavonol Low vs Mid Heights
## [1] 0.0352653
  • ANOVA Flavonol High vs Low Heights
## Analysis of Variance Table
## 
## Response: HH$Flav
##            Df  Sum Sq   Mean Sq F value Pr(>F)
## HL$Flav     1 0.00651 0.0065076   0.373 0.5423
## Residuals 157 2.73937 0.0174482

  • R.squared Flavonol High vs Low Heights
## [1] 0.002369954

Row Plots

Anthocyanin

## Warning: Removed 21 rows containing non-finite values (stat_boxplot).

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Anth5
##             Df  Sum Sq    Mean Sq F value Pr(>F)
## F1$Row      49 0.00009 0.00000191  0.0011      1
## Residuals 1740 3.03249 0.00174281

## 
## Call:
## lm(formula = F1$Anth5 ~ F1$Row)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.10823 -0.02772 -0.00075  0.02580  0.19883 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)
## (Intercept) -1.236e-04  6.026e-03  -0.021    0.984
## F1$Row10    -4.004e-04  9.527e-03  -0.042    0.966
## F1$Row11     1.971e-06  8.478e-03   0.000    1.000
## F1$Row12     2.002e-04  9.527e-03   0.021    0.983
## F1$Row13     6.312e-05  9.819e-03   0.006    0.995
## F1$Row14     1.970e-04  9.440e-03   0.021    0.983
## F1$Row15     1.970e-04  9.440e-03   0.021    0.983
## F1$Row16     1.123e-05  9.716e-03   0.001    0.999
## F1$Row17     5.573e-04  1.092e-02   0.051    0.959
## F1$Row18     1.123e-05  9.716e-03   0.001    0.999
## F1$Row19     1.970e-04  9.440e-03   0.021    0.983
## F1$Row2      1.970e-04  9.440e-03   0.021    0.983
## F1$Row20     6.273e-05  8.766e-03   0.007    0.994
## F1$Row21     1.432e-04  9.133e-03   0.016    0.987
## F1$Row22     1.970e-04  9.440e-03   0.021    0.983
## F1$Row23     6.273e-05  8.766e-03   0.007    0.994
## F1$Row24     6.013e-04  9.440e-03   0.064    0.949
## F1$Row25     1.970e-04  9.440e-03   0.021    0.983
## F1$Row26     6.852e-04  9.619e-03   0.071    0.943
## F1$Row27     4.335e-04  9.527e-03   0.045    0.964
## F1$Row28     1.970e-04  9.440e-03   0.021    0.983
## F1$Row29    -4.004e-04  9.527e-03  -0.042    0.966
## F1$Row3      1.970e-04  9.440e-03   0.021    0.983
## F1$Row30    -1.846e-04  9.716e-03  -0.019    0.985
## F1$Row31    -4.212e-04  8.766e-03  -0.048    0.962
## F1$Row32     1.970e-04  8.713e-03   0.023    0.982
## F1$Row33     1.970e-04  9.440e-03   0.021    0.983
## F1$Row34     1.970e-04  8.713e-03   0.023    0.982
## F1$Row35     2.890e-05  8.662e-03   0.003    0.997
## F1$Row36     2.002e-04  9.527e-03   0.021    0.983
## F1$Row37     2.002e-04  9.527e-03   0.021    0.983
## F1$Row38    -1.756e-04  9.619e-03  -0.018    0.985
## F1$Row39     1.970e-04  9.440e-03   0.021    0.983
## F1$Row4     -2.072e-04  9.440e-03  -0.022    0.982
## F1$Row40     1.970e-04  9.440e-03   0.021    0.983
## F1$Row41     3.156e-04  8.567e-03   0.037    0.971
## F1$Row42     3.751e-04  9.440e-03   0.040    0.968
## F1$Row43     2.548e-04  9.619e-03   0.026    0.979
## F1$Row44     4.335e-04  9.527e-03   0.045    0.964
## F1$Row45     6.273e-05  8.766e-03   0.007    0.994
## F1$Row46     5.096e-04  8.766e-03   0.058    0.954
## F1$Row47    -1.109e-04  8.766e-03  -0.013    0.990
## F1$Row48     1.899e-05  9.440e-03   0.002    0.998
## F1$Row49     1.970e-04  8.713e-03   0.023    0.982
## F1$Row5      2.002e-04  9.527e-03   0.021    0.983
## F1$Row50    -1.715e-04  8.178e-03  -0.021    0.983
## F1$Row6      1.970e-04  9.440e-03   0.021    0.983
## F1$Row7      1.970e-04  9.440e-03   0.021    0.983
## F1$Row8      1.970e-04  9.440e-03   0.021    0.983
## F1$Row9     -2.550e-05  9.358e-03  -0.003    0.998
## 
## Residual standard error: 0.04175 on 1740 degrees of freedom
##   (21 observations deleted due to missingness)
## Multiple R-squared:  3.078e-05,  Adjusted R-squared:  -0.02813 
## F-statistic: 0.001093 on 49 and 1740 DF,  p-value: 1
  • R.squared
## [1] 3.078204e-05

Chlorophyll

## Warning: Removed 21 rows containing non-finite values (stat_boxplot).

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Chl5
##             Df Sum Sq Mean Sq F value Pr(>F)
## F1$Row      49      0    0.00       0      1
## Residuals 1740 388434  223.24

## 
## Call:
## lm(formula = F1$Chl5 ~ F1$Row)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -40.413 -10.889   1.258  11.488  30.448 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)
## (Intercept)  5.122e-14  2.157e+00       0        1
## F1$Row10    -5.443e-14  3.410e+00       0        1
## F1$Row11    -5.868e-14  3.034e+00       0        1
## F1$Row12    -4.608e-14  3.410e+00       0        1
## F1$Row13    -4.346e-14  3.514e+00       0        1
## F1$Row14    -4.472e-14  3.379e+00       0        1
## F1$Row15    -5.143e-14  3.379e+00       0        1
## F1$Row16    -4.709e-14  3.477e+00       0        1
## F1$Row17    -2.396e-14  3.909e+00       0        1
## F1$Row18    -4.307e-14  3.477e+00       0        1
## F1$Row19    -8.068e-14  3.379e+00       0        1
## F1$Row2     -3.876e-14  3.379e+00       0        1
## F1$Row20    -5.483e-14  3.137e+00       0        1
## F1$Row21    -5.324e-14  3.269e+00       0        1
## F1$Row22    -5.665e-14  3.379e+00       0        1
## F1$Row23    -5.097e-14  3.137e+00       0        1
## F1$Row24    -3.762e-14  3.379e+00       0        1
## F1$Row25    -4.563e-14  3.379e+00       0        1
## F1$Row26    -5.032e-14  3.443e+00       0        1
## F1$Row27    -5.458e-14  3.410e+00       0        1
## F1$Row28    -4.724e-14  3.379e+00       0        1
## F1$Row29    -3.408e-14  3.410e+00       0        1
## F1$Row3     -4.192e-14  3.379e+00       0        1
## F1$Row30    -5.594e-14  3.477e+00       0        1
## F1$Row31     1.341e-14  3.137e+00       0        1
## F1$Row32    -5.711e-14  3.118e+00       0        1
## F1$Row33    -5.905e-14  3.379e+00       0        1
## F1$Row34    -5.094e-14  3.118e+00       0        1
## F1$Row35    -6.647e-14  3.100e+00       0        1
## F1$Row36    -5.311e-14  3.410e+00       0        1
## F1$Row37    -9.871e-15  3.410e+00       0        1
## F1$Row38    -4.983e-14  3.443e+00       0        1
## F1$Row39    -5.183e-14  3.379e+00       0        1
## F1$Row4     -5.165e-14  3.379e+00       0        1
## F1$Row40    -6.223e-14  3.379e+00       0        1
## F1$Row41    -5.581e-14  3.066e+00       0        1
## F1$Row42    -5.669e-14  3.379e+00       0        1
## F1$Row43    -5.319e-14  3.443e+00       0        1
## F1$Row44    -7.369e-14  3.410e+00       0        1
## F1$Row45    -6.561e-14  3.137e+00       0        1
## F1$Row46    -8.051e-14  3.137e+00       0        1
## F1$Row47    -6.965e-14  3.137e+00       0        1
## F1$Row48    -6.373e-14  3.379e+00       0        1
## F1$Row49    -4.888e-14  3.118e+00       0        1
## F1$Row5     -6.082e-14  3.410e+00       0        1
## F1$Row50    -6.229e-14  2.927e+00       0        1
## F1$Row6     -4.716e-14  3.379e+00       0        1
## F1$Row7     -6.638e-14  3.379e+00       0        1
## F1$Row8     -6.942e-14  3.379e+00       0        1
## F1$Row9     -7.645e-14  3.349e+00       0        1
## 
## Residual standard error: 14.94 on 1740 degrees of freedom
##   (21 observations deleted due to missingness)
## Multiple R-squared:  1.668e-29,  Adjusted R-squared:  -0.02816 
## F-statistic: 5.924e-28 on 49 and 1740 DF,  p-value: 1
  • R.squared
## [1] 1.668271e-29

Flavonol

## Warning: Removed 21 rows containing non-finite values (stat_boxplot).

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Flav5
##             Df Sum Sq  Mean Sq F value Pr(>F)
## F1$Row      49  0.200 0.004090  0.0723      1
## Residuals 1740 98.459 0.056585

## 
## Call:
## lm(formula = F1$Flav5 ~ F1$Row)
## 
## Residuals:
##      Min       1Q   Median       3Q      Max 
## -0.87631 -0.14319  0.01576  0.15006  0.83162 
## 
## Coefficients:
##               Estimate Std. Error t value Pr(>|t|)
## (Intercept) -0.0160350  0.0343346  -0.467    0.641
## F1$Row10     0.0122635  0.0542877   0.226    0.821
## F1$Row11    -0.0007709  0.0483081  -0.016    0.987
## F1$Row12     0.0109164  0.0542877   0.201    0.841
## F1$Row13     0.0113525  0.0559472   0.203    0.839
## F1$Row14     0.0109282  0.0537920   0.203    0.839
## F1$Row15     0.0109282  0.0537920   0.203    0.839
## F1$Row16     0.0159958  0.0553629   0.289    0.773
## F1$Row17     0.0285742  0.0622367   0.459    0.646
## F1$Row18     0.0110881  0.0553629   0.200    0.841
## F1$Row19     0.0109282  0.0537920   0.203    0.839
## F1$Row2      0.0109282  0.0537920   0.203    0.839
## F1$Row20     0.0175783  0.0499480   0.352    0.725
## F1$Row21     0.0067765  0.0520404   0.130    0.896
## F1$Row22     0.0109282  0.0537920   0.203    0.839
## F1$Row23     0.0370839  0.0499480   0.742    0.458
## F1$Row24     0.0073530  0.0537920   0.137    0.891
## F1$Row25     0.0109282  0.0537920   0.203    0.839
## F1$Row26     0.0089356  0.0548106   0.163    0.871
## F1$Row27     0.0094440  0.0542877   0.174    0.862
## F1$Row28     0.0109282  0.0537920   0.203    0.839
## F1$Row29     0.0147885  0.0542877   0.272    0.785
## F1$Row3      0.0109282  0.0537920   0.203    0.839
## F1$Row30     0.0118640  0.0553629   0.214    0.830
## F1$Row31     0.0048055  0.0499480   0.096    0.923
## F1$Row32     0.0352480  0.0496477   0.710    0.478
## F1$Row33     0.0109282  0.0537920   0.203    0.839
## F1$Row34     0.0352480  0.0496477   0.710    0.478
## F1$Row35     0.0346724  0.0493591   0.702    0.482
## F1$Row36     0.0124501  0.0542877   0.229    0.819
## F1$Row37     0.0124501  0.0542877   0.229    0.819
## F1$Row38     0.0128693  0.0548106   0.235    0.814
## F1$Row39     0.0109282  0.0537920   0.203    0.839
## F1$Row4      0.0125355  0.0537920   0.233    0.816
## F1$Row40     0.0109282  0.0537920   0.203    0.839
## F1$Row41     0.0218259  0.0488140   0.447    0.655
## F1$Row42     0.0107487  0.0537920   0.200    0.842
## F1$Row43     0.0095752  0.0548106   0.175    0.861
## F1$Row44     0.0109777  0.0542877   0.202    0.840
## F1$Row45     0.0359426  0.0499480   0.720    0.472
## F1$Row46     0.0357126  0.0499480   0.715    0.475
## F1$Row47     0.0350335  0.0499480   0.701    0.483
## F1$Row48     0.0106271  0.0537920   0.198    0.843
## F1$Row49     0.0352480  0.0496477   0.710    0.478
## F1$Row5      0.0124501  0.0542877   0.229    0.819
## F1$Row50     0.0200420  0.0466003   0.430    0.667
## F1$Row6      0.0109282  0.0537920   0.203    0.839
## F1$Row7      0.0109282  0.0537920   0.203    0.839
## F1$Row8      0.0109282  0.0537920   0.203    0.839
## F1$Row9      0.0123251  0.0533211   0.231    0.817
## 
## Residual standard error: 0.2379 on 1740 degrees of freedom
##   (21 observations deleted due to missingness)
## Multiple R-squared:  0.002032,   Adjusted R-squared:  -0.02607 
## F-statistic: 0.07229 on 49 and 1740 DF,  p-value: 1
  • R.squared
## [1] 0.002031552

Height 2018

## Warning: Removed 89 rows containing non-finite values (stat_boxplot).

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$H185
##             Df Sum Sq Mean Sq F value    Pr(>F)    
## F1$Row      49  24288  495.68  2.1009 1.659e-05 ***
## Residuals 1672 394486  235.94                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

## 
## Call:
## lm(formula = F1$H185 ~ F1$Row)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -52.933 -11.518  -0.736  11.531  39.018 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   8.5699     2.5252   3.394 0.000706 ***
## F1$Row10     -7.3312     3.7081  -1.977 0.048195 *  
## F1$Row11     -4.5365     3.3454  -1.356 0.175273    
## F1$Row12     -6.7638     3.7081  -1.824 0.068317 .  
## F1$Row13     -6.0953     3.8095  -1.600 0.109780    
## F1$Row14     -7.1737     3.6778  -1.951 0.051279 .  
## F1$Row15     -0.6156     4.1353  -0.149 0.881685    
## F1$Row16     -7.9814     3.7738  -2.115 0.034581 *  
## F1$Row17    -10.2487     4.1353  -2.478 0.013299 *  
## F1$Row18     -5.8621     3.7738  -1.553 0.120521    
## F1$Row19     -7.1737     3.6778  -1.951 0.051279 .  
## F1$Row2      -7.1737     3.6778  -1.951 0.051279 .  
## F1$Row20     -6.0017     3.4444  -1.742 0.081610 .  
## F1$Row21     -7.0921     3.5476  -1.999 0.045758 *  
## F1$Row22     -8.0326     3.6491  -2.201 0.027854 *  
## F1$Row23    -14.8322     3.4444  -4.306 1.76e-05 ***
## F1$Row24     -7.9433     3.6491  -2.177 0.029636 *  
## F1$Row25     -8.0326     3.6491  -2.201 0.027854 *  
## F1$Row26     -8.4962     3.7081  -2.291 0.022071 *  
## F1$Row27    -11.9432     4.1353  -2.888 0.003926 ** 
## F1$Row28     -8.0326     3.6491  -2.201 0.027854 *  
## F1$Row29    -10.9642     4.1966  -2.613 0.009066 ** 
## F1$Row3      -7.1737     3.6778  -1.951 0.051279 .  
## F1$Row30     -8.7014     3.7400  -2.327 0.020106 *  
## F1$Row31     -6.0018     3.4262  -1.752 0.080001 .  
## F1$Row32    -14.4746     3.4262  -4.225 2.52e-05 ***
## F1$Row33     -8.0326     3.6491  -2.201 0.027854 *  
## F1$Row34    -14.4746     3.4262  -4.225 2.52e-05 ***
## F1$Row35    -14.1328     3.4088  -4.146 3.55e-05 ***
## F1$Row36     -8.3034     3.6778  -2.258 0.024093 *  
## F1$Row37     -8.3034     3.6778  -2.258 0.024093 *  
## F1$Row38     -7.9288     3.7081  -2.138 0.032640 *  
## F1$Row39     -2.1704     4.0786  -0.532 0.594691    
## F1$Row4      -0.6156     4.1353  -0.149 0.881685    
## F1$Row40     -2.1704     4.0786  -0.532 0.594691    
## F1$Row41    -11.1135     3.3759  -3.292 0.001015 ** 
## F1$Row42     -8.0326     3.6491  -2.201 0.027854 *  
## F1$Row43     -7.2665     3.7081  -1.960 0.050201 .  
## F1$Row44     -8.3034     3.6778  -2.258 0.024093 *  
## F1$Row45    -14.3393     3.4444  -4.163 3.30e-05 ***
## F1$Row46    -14.8322     3.4444  -4.306 1.76e-05 ***
## F1$Row47    -13.9652     3.4444  -4.055 5.25e-05 ***
## F1$Row48     -8.5666     3.6491  -2.348 0.019011 *  
## F1$Row49    -14.4746     3.4262  -4.225 2.52e-05 ***
## F1$Row5      -0.6879     4.1966  -0.164 0.869820    
## F1$Row50    -10.3134     3.2428  -3.180 0.001498 ** 
## F1$Row6      -7.1737     3.6778  -1.951 0.051279 .  
## F1$Row7      -7.1737     3.6778  -1.951 0.051279 .  
## F1$Row8      -7.1737     3.6778  -1.951 0.051279 .  
## F1$Row9      -7.5595     3.6491  -2.072 0.038456 *  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 15.36 on 1672 degrees of freedom
##   (89 observations deleted due to missingness)
## Multiple R-squared:  0.058,  Adjusted R-squared:  0.03039 
## F-statistic: 2.101 on 49 and 1672 DF,  p-value: 1.659e-05
  • R.squared
## [1] 0.05799867

Height 2019

## Warning: Removed 90 rows containing non-finite values (stat_boxplot).

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$H195
##             Df Sum Sq Mean Sq F value    Pr(>F)    
## F1$Row      49  36836  751.76  3.2009 1.777e-12 ***
## Residuals 1671 392453  234.86                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

## 
## Call:
## lm(formula = F1$H195 ~ F1$Row)
## 
## Residuals:
##     Min      1Q  Median      3Q     Max 
## -47.068  -9.354   1.204  10.862  38.322 
## 
## Coefficients:
##             Estimate Std. Error t value Pr(>|t|)    
## (Intercept)   12.495      2.519   4.959 7.79e-07 ***
## F1$Row10     -11.677      3.700  -3.156 0.001626 ** 
## F1$Row11      -7.027      3.338  -2.105 0.035411 *  
## F1$Row12     -10.852      3.700  -2.933 0.003399 ** 
## F1$Row13      -9.877      3.801  -2.599 0.009444 ** 
## F1$Row14     -11.478      3.669  -3.128 0.001791 ** 
## F1$Row15      -1.467      4.126  -0.356 0.722127    
## F1$Row16     -12.841      3.765  -3.410 0.000664 ***
## F1$Row17     -17.664      4.187  -4.219 2.59e-05 ***
## F1$Row18      -9.476      3.765  -2.517 0.011939 *  
## F1$Row19     -11.478      3.669  -3.128 0.001791 ** 
## F1$Row2      -11.478      3.669  -3.128 0.001791 ** 
## F1$Row20      -9.992      3.436  -2.908 0.003691 ** 
## F1$Row21     -10.820      3.540  -3.057 0.002272 ** 
## F1$Row22     -12.346      3.641  -3.391 0.000713 ***
## F1$Row23     -19.346      3.436  -5.629 2.12e-08 ***
## F1$Row24     -12.133      3.641  -3.333 0.000879 ***
## F1$Row25     -12.346      3.641  -3.391 0.000713 ***
## F1$Row26     -13.026      3.700  -3.521 0.000442 ***
## F1$Row27     -18.724      4.126  -4.538 6.08e-06 ***
## F1$Row28     -12.346      3.641  -3.391 0.000713 ***
## F1$Row29     -15.926      4.187  -3.804 0.000148 ***
## F1$Row3      -11.478      3.669  -3.128 0.001791 ** 
## F1$Row30     -13.282      3.731  -3.559 0.000382 ***
## F1$Row31      -9.051      3.418  -2.648 0.008180 ** 
## F1$Row32     -18.857      3.418  -5.516 4.00e-08 ***
## F1$Row33     -12.346      3.641  -3.391 0.000713 ***
## F1$Row34     -18.857      3.418  -5.516 4.00e-08 ***
## F1$Row35     -18.390      3.401  -5.407 7.32e-08 ***
## F1$Row36     -12.785      3.669  -3.484 0.000506 ***
## F1$Row37     -12.785      3.669  -3.484 0.000506 ***
## F1$Row38     -12.200      3.700  -3.298 0.000995 ***
## F1$Row39      -3.186      4.069  -0.783 0.433764    
## F1$Row4       -1.467      4.126  -0.356 0.722127    
## F1$Row40      -3.186      4.069  -0.783 0.433764    
## F1$Row41     -14.762      3.368  -4.383 1.24e-05 ***
## F1$Row42     -12.346      3.641  -3.391 0.000713 ***
## F1$Row43     -11.149      3.700  -3.014 0.002621 ** 
## F1$Row44     -12.785      3.669  -3.484 0.000506 ***
## F1$Row45     -18.563      3.436  -5.402 7.55e-08 ***
## F1$Row46     -19.346      3.436  -5.629 2.12e-08 ***
## F1$Row47     -18.342      3.436  -5.337 1.07e-07 ***
## F1$Row48     -13.123      3.641  -3.604 0.000322 ***
## F1$Row49     -18.857      3.418  -5.516 4.00e-08 ***
## F1$Row5       -1.640      4.187  -0.392 0.695367    
## F1$Row50     -13.308      3.235  -4.113 4.09e-05 ***
## F1$Row6      -11.478      3.669  -3.128 0.001791 ** 
## F1$Row7      -11.478      3.669  -3.128 0.001791 ** 
## F1$Row8      -11.478      3.669  -3.128 0.001791 ** 
## F1$Row9      -12.067      3.641  -3.314 0.000938 ***
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
## 
## Residual standard error: 15.33 on 1671 degrees of freedom
##   (90 observations deleted due to missingness)
## Multiple R-squared:  0.08581,    Adjusted R-squared:  0.059 
## F-statistic: 3.201 on 49 and 1671 DF,  p-value: 1.777e-12
  • R.squared
## [1] 0.08580726

Height Difference 2018-2019

## Warning: Removed 90 rows containing non-finite values (stat_boxplot).

## Warning: Removed 50 rows containing missing values (geom_point).

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$HD5
##             Df Sum Sq Mean Sq F value Pr(>F)
## F1$Row      49   2380  48.577  0.2137      1
## Residuals 1671 379803 227.291

+R.squared

## [1] 0.00593089

Column Plots

Anthocyanin

## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing non-finite values (stat_summary).

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Anth5
##             Df  Sum Sq    Mean Sq F value Pr(>F)
## F1$Column    3 0.00038 0.00012737   0.074 0.9739
## Residuals 1786 3.07332 0.00172078

  • R.squared
## [1] 0.0001243198

Chlorophyll

## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing non-finite values (stat_summary).

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Chl5
##             Df Sum Sq Mean Sq F value Pr(>F)
## F1$Column    3    198  65.844  0.3043 0.8223
## Residuals 1786 386473 216.390

  • R.squared
## [1] 0.0005108494

Flavonol

## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing non-finite values (stat_summary).

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Flav5
##             Df Sum Sq  Mean Sq F value Pr(>F)
## F1$Column    3  0.012 0.004060  0.0728 0.9746
## Residuals 1786 99.618 0.055777

  • R.squared
## [1] 0.0001222632

Height 2018

## Warning: Removed 89 rows containing non-finite values (stat_boxplot).
## Warning: Removed 89 rows containing non-finite values (stat_summary).

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$H185
##             Df Sum Sq Mean Sq F value    Pr(>F)    
## F1$Column    3  15817  5272.4  22.479 2.826e-14 ***
## Residuals 1718 402957   234.6                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared
## [1] 0.03776989

Height 2019

## Warning: Removed 90 rows containing non-finite values (stat_boxplot).
## Warning: Removed 90 rows containing non-finite values (stat_summary).

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$H195
##             Df Sum Sq Mean Sq F value    Pr(>F)    
## F1$Column    3  23664  7887.8  33.389 < 2.2e-16 ***
## Residuals 1717 405626   236.2                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared
## [1] 0.05512251

Height Difference 2018-2019

## Warning: Removed 90 rows containing non-finite values (stat_boxplot).
## Warning: Removed 90 rows containing non-finite values (stat_summary).

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$HD5
##             Df Sum Sq Mean Sq F value  Pr(>F)  
## F1$Column    3   1938  646.10  2.9175 0.03306 *
## Residuals 1717 380245  221.46                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared
## [1] 0.005124903

Flowering and Flowering Levels

Flowering refers to presence or not of flowers, Flower Level refers to a measure relating to the number of flowers present (0 = no flowers, 1 = 1-10, 2 = 10-20, 3 = 20+)

Anthocyanin

## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing non-finite values (stat_summary).

  • ANOVA Flowering Level
## Analysis of Variance Table
## 
## Response: F1$Anth5
##                   Df Sum Sq    Mean Sq F value Pr(>F)
## F1$Flower.Level    3 0.0028 0.00093363   0.543 0.6529
## Residuals       1786 3.0709 0.00171943

  • R.squared Flowering Level
## [1] 0.0009112453
  • T.tests comparing Flowering Levels and Anthocyanin
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$Anth and FLWR1$Anth
## t = 0.025664, df = 17.375, p-value = 0.9798
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.008423762  0.008631570
## sample estimates:
##     mean of x     mean of y 
## -0.0001864908 -0.0002903948
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$Anth and FLWR2$Anth
## t = 0.2922, df = 10.049, p-value = 0.7761
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.006353989  0.008273500
## sample estimates:
##     mean of x     mean of y 
## -0.0001864908 -0.0011462463
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$Anth and FLWR3$Anth
## t = -1.1298, df = 10.172, p-value = 0.2845
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.014848706  0.004841807
## sample estimates:
##     mean of x     mean of y 
## -0.0001864908  0.0048169586
## 
##  Welch Two Sample t-test
## 
## data:  FLWR1$Anth and FLWR2$Anth
## t = 0.1717, df = 22.843, p-value = 0.8652
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.009459314  0.011171017
## sample estimates:
##     mean of x     mean of y 
## -0.0002903948 -0.0011462463
## 
##  Welch Two Sample t-test
## 
## data:  FLWR1$Anth and FLWR3$Anth
## t = -0.88018, df = 21.286, p-value = 0.3886
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.017164673  0.006949967
## sample estimates:
##     mean of x     mean of y 
## -0.0002903948  0.0048169586
## 
##  Welch Two Sample t-test
## 
## data:  FLWR2$Anth and FLWR3$Anth
## t = -1.1256, df = 15.954, p-value = 0.277
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.017196954  0.005270544
## sample estimates:
##    mean of x    mean of y 
## -0.001146246  0.004816959
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing non-finite values (stat_summary).

  • ANOVA Flowering Presence
## Analysis of Variance Table
## 
## Response: F1$Anth5
##             Df  Sum Sq    Mean Sq F value Pr(>F)
## F1$Flower    1 0.00039 0.00039351  0.2289 0.6324
## Residuals 1788 3.07330 0.00171885

  • R.squared Flowering Presence
## [1] 0.0001280242

Chlorophyll

## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing non-finite values (stat_summary).

  • ANOVA Flowering Level
## Analysis of Variance Table
## 
## Response: F1$Chl5
##                   Df Sum Sq Mean Sq F value  Pr(>F)  
## F1$Flower.Level    3   1461  487.00  2.2579 0.07985 .
## Residuals       1786 385210  215.68                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared Flowering Level
## [1] 0.003778413
  • T.tests comparing Flowering Levels and Chlorophyll
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$Chl and FLWR1$Chl
## t = -1.3501, df = 18.737, p-value = 0.1931
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -3.4526591  0.7464858
## sample estimates:
##  mean of x  mean of y 
## -0.2203429  1.1327437
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$Chl and FLWR2$Chl
## t = -3.0493, df = 9.63, p-value = 0.01279
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -5.7911270 -0.8863768
## sample estimates:
##  mean of x  mean of y 
## -0.2203429  3.1184090
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$Chl and FLWR3$Chl
## t = 0.70751, df = 10.428, p-value = 0.4948
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -1.844508  3.574981
## sample estimates:
##  mean of x  mean of y 
## -0.2203429 -1.0855790
## 
##  Welch Two Sample t-test
## 
## data:  FLWR1$Chl and FLWR2$Chl
## t = -1.4075, df = 19.522, p-value = 0.175
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -4.9330444  0.9617139
## sample estimates:
## mean of x mean of y 
##  1.132744  3.118409
## 
##  Welch Two Sample t-test
## 
## data:  FLWR1$Chl and FLWR3$Chl
## t = 1.4669, df = 19.505, p-value = 0.1583
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.9413134  5.3779589
## sample estimates:
## mean of x mean of y 
##  1.132744 -1.085579
## 
##  Welch Two Sample t-test
## 
## data:  FLWR2$Chl and FLWR3$Chl
## t = 2.6688, df = 16.937, p-value = 0.01623
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  0.8795891 7.5283869
## sample estimates:
## mean of x mean of y 
##  3.118409 -1.085579
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing non-finite values (stat_summary).

  • ANOVA Flowering Presence
## Analysis of Variance Table
## 
## Response: F1$Chl5
##             Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower    1     19  18.847  0.0872 0.7679
## Residuals 1788 386652 216.248

  • R.squared Flowering Presence
## [1] 4.87422e-05

Flavonol

## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing non-finite values (stat_summary).

  • ANOVA Flowering Levels
## Analysis of Variance Table
## 
## Response: F1$Flav5
##                   Df Sum Sq  Mean Sq F value  Pr(>F)  
## F1$Flower.Level    3  0.574 0.191220  3.4477 0.01606 *
## Residuals       1786 99.056 0.055463                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared Flowering Levels
## [1] 0.005757915
  • T.tests comparing Flowering Levels and Flavonol
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$Flav and FLWR1$Flav
## t = -0.19352, df = 20.332, p-value = 0.8485
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.04944842  0.04104444
## sample estimates:
##     mean of x     mean of y 
## -0.0047609014 -0.0005589119
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$Flav and FLWR2$Flav
## t = -2.2376, df = 8.9795, p-value = 0.05211
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.1555838602  0.0008748158
## sample estimates:
##    mean of x    mean of y 
## -0.004760901  0.072593621
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$Flav and FLWR3$Flav
## t = -0.58781, df = 9.9953, p-value = 0.5697
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.10202255  0.05943198
## sample estimates:
##    mean of x    mean of y 
## -0.004760901  0.016534383
## 
##  Welch Two Sample t-test
## 
## data:  FLWR1$Flav and FLWR2$Flav
## t = -1.8689, df = 13.816, p-value = 0.08299
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.15721039  0.01090532
## sample estimates:
##     mean of x     mean of y 
## -0.0005589119  0.0725936208
## 
##  Welch Two Sample t-test
## 
## data:  FLWR1$Flav and FLWR3$Flav
## t = -0.42086, df = 14.853, p-value = 0.6799
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.1037374  0.0695508
## sample estimates:
##     mean of x     mean of y 
## -0.0005589119  0.0165343828
## 
##  Welch Two Sample t-test
## 
## data:  FLWR2$Flav and FLWR3$Flav
## t = 1.1508, df = 16.999, p-value = 0.2658
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -0.04672184  0.15884031
## sample estimates:
##  mean of x  mean of y 
## 0.07259362 0.01653438
## Warning: Removed 21 rows containing non-finite values (stat_boxplot).
## Warning: Removed 21 rows containing non-finite values (stat_summary).

  • ANOVA Flowering Presence
## Analysis of Variance Table
## 
## Response: F1$Flav5
##             Df Sum Sq  Mean Sq F value  Pr(>F)  
## F1$Flower    1   0.24 0.240050  4.3184 0.03784 *
## Residuals 1788  99.39 0.055587                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared Flowering Presence
## [1] 0.002409418

Height 2018

## Warning: Removed 89 rows containing non-finite values (stat_boxplot).
## Warning: Removed 89 rows containing non-finite values (stat_summary).

  • ANOVA Flowering Levels
## Analysis of Variance Table
## 
## Response: F1$H185
##                   Df Sum Sq Mean Sq F value    Pr(>F)    
## F1$Flower.Level    3  11639  3879.6  16.371 1.718e-10 ***
## Residuals       1718 407135   237.0                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared Flowering Levels
## [1] 0.02779275
  • T.tests comparing Flowering Levels and 2018 Height
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$H18 and FLWR1$H18
## t = -1.6305, df = 17.703, p-value = 0.1207
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -18.48037   2.34066
## sample estimates:
## mean of x mean of y 
## -2.410131  5.659726
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$H18 and FLWR2$H18
## t = -0.81929, df = 6.4906, p-value = 0.4417
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -22.95103  11.27931
## sample estimates:
## mean of x mean of y 
## -2.410131  3.425728
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$H18 and FLWR3$H18
## t = -1.5807, df = 9.3853, p-value = 0.147
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -19.310608   3.365938
## sample estimates:
## mean of x mean of y 
## -2.410131  5.562204
## 
##  Welch Two Sample t-test
## 
## data:  FLWR1$H18 and FLWR2$H18
## t = 0.26453, df = 11.816, p-value = 0.7959
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -16.19812  20.66612
## sample estimates:
## mean of x mean of y 
##  5.659726  3.425728
## 
##  Welch Two Sample t-test
## 
## data:  FLWR1$H18 and FLWR3$H18
## t = 0.014376, df = 20.604, p-value = 0.9887
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -14.02649  14.22153
## sample estimates:
## mean of x mean of y 
##  5.659726  5.562204
## 
##  Welch Two Sample t-test
## 
## data:  FLWR2$H18 and FLWR3$H18
## t = -0.25133, df = 11.217, p-value = 0.8061
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -20.80233  16.52937
## sample estimates:
## mean of x mean of y 
##  3.425728  5.562204
## Warning: Removed 89 rows containing non-finite values (stat_boxplot).
## Warning: Removed 89 rows containing non-finite values (stat_summary).

  • ANOVA Flower Presence
## Analysis of Variance Table
## 
## Response: F1$H185
##             Df Sum Sq Mean Sq F value   Pr(>F)   
## F1$Flower    1   2126 2125.89   8.776 0.003094 **
## Residuals 1720 416648  242.24                    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared Flower Presence
## [1] 0.005076449

Height 2019

## Warning: Removed 90 rows containing non-finite values (stat_boxplot).
## Warning: Removed 90 rows containing non-finite values (stat_summary).

  • ANOVA Flowering Level
## Analysis of Variance Table
## 
## Response: F1$H195
##                   Df Sum Sq Mean Sq F value    Pr(>F)    
## F1$Flower.Level    3   8766 2922.09  11.931 9.858e-08 ***
## Residuals       1717 420523  244.92                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared Flowering Level
## [1] 0.02042042
  • T.tests comparing Flowering Levels and 2019 Height
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$H19 and FLWR1$H19
## t = -1.7634, df = 18.363, p-value = 0.09447
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -17.725963   1.535942
## sample estimates:
## mean of x mean of y 
## -1.992529  6.102482
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$H19 and FLWR2$H19
## t = -0.12465, df = 6.2813, p-value = 0.9047
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -24.14341  21.77867
## sample estimates:
##  mean of x  mean of y 
## -1.9925285 -0.8101606
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$H19 and FLWR3$H19
## t = 0.3993, df = 9.2524, p-value = 0.6987
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -9.983022 14.284387
## sample estimates:
## mean of x mean of y 
## -1.992529 -4.143211
## 
##  Welch Two Sample t-test
## 
## data:  FLWR1$H19 and FLWR2$H19
## t = 0.66835, df = 8.7152, p-value = 0.5212
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -16.60158  30.42687
## sample estimates:
##  mean of x  mean of y 
##  6.1024818 -0.8101606
## 
##  Welch Two Sample t-test
## 
## data:  FLWR1$H19 and FLWR3$H19
## t = 1.5106, df = 18.391, p-value = 0.1479
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -3.982633 24.474019
## sample estimates:
## mean of x mean of y 
##  6.102482 -4.143211
## 
##  Welch Two Sample t-test
## 
## data:  FLWR2$H19 and FLWR3$H19
## t = 0.31093, df = 9.5696, p-value = 0.7625
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -20.69819  27.36429
## sample estimates:
##  mean of x  mean of y 
## -0.8101606 -4.1432112
## Warning: Removed 89 rows containing non-finite values (stat_boxplot).
## Warning: Removed 89 rows containing non-finite values (stat_summary).

  • ANOVA Flower Presence
## Analysis of Variance Table
## 
## Response: F1$H195
##             Df Sum Sq Mean Sq F value Pr(>F)
## F1$Flower    1    343  342.61   1.373 0.2415
## Residuals 1719 428947  249.53

  • R.squared Flower Presence
## [1] 0.0007980757

Height Difference 2018-2019

## Warning: Removed 90 rows containing non-finite values (stat_boxplot).
## Warning: Removed 90 rows containing non-finite values (stat_summary).

  • ANOVA Flowering Level
## Analysis of Variance Table
## 
## Response: F1$HD5
##                   Df Sum Sq Mean Sq F value    Pr(>F)    
## F1$Flower.Level    3  11642  3880.7  17.982 1.719e-11 ***
## Residuals       1717 370541   215.8                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared Flowering Level
## [1] 0.0305669
  • T.tests comparing Flowering Levels and 2018-19 Height Differences
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$HD5 and FLWR1$HD5
## t = 0.0726, df = 22.1, p-value = 0.9428
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -6.781665  7.273837
## sample estimates:
## mean of x mean of y 
## 0.6780263 0.4319402
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$HD5 and FLWR2$HD5
## t = 1.4803, df = 9.0022, p-value = 0.1729
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -2.604488 12.467963
## sample estimates:
##  mean of x  mean of y 
##  0.6780263 -4.2537116
## 
##  Welch Two Sample t-test
## 
## data:  FLWR0$HD5 and FLWR3$HD5
## t = 2.0307, df = 9.4119, p-value = 0.07149
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -1.10757 21.88518
## sample estimates:
##  mean of x  mean of y 
##  0.6780263 -9.7107801
## 
##  Welch Two Sample t-test
## 
## data:  FLWR1$HD5 and FLWR2$HD5
## t = 1.0896, df = 17.451, p-value = 0.2907
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -4.369425 13.740729
## sample estimates:
##  mean of x  mean of y 
##  0.4319402 -4.2537116
## 
##  Welch Two Sample t-test
## 
## data:  FLWR1$HD5 and FLWR3$HD5
## t = 1.7507, df = 14.317, p-value = 0.1014
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -2.257682 22.543123
## sample estimates:
##  mean of x  mean of y 
##  0.4319402 -9.7107801
## 
##  Welch Two Sample t-test
## 
## data:  FLWR2$HD5 and FLWR3$HD5
## t = 0.94742, df = 12.738, p-value = 0.3611
## alternative hypothesis: true difference in means is not equal to 0
## 95 percent confidence interval:
##  -7.012502 17.926639
## sample estimates:
## mean of x mean of y 
## -4.253712 -9.710780
## Warning: Removed 90 rows containing non-finite values (stat_boxplot).
## Warning: Removed 90 rows containing non-finite values (stat_summary).

  • ANOVA Flowering Presence
## Analysis of Variance Table
## 
## Response: F1$HD5
##             Df Sum Sq Mean Sq F value    Pr(>F)    
## F1$Flower    1   4205  4205.2  19.125 1.298e-05 ***
## Residuals 1719 377978   219.9                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared Flowering Presence
## [1] 0.01111171

Measure Correlations

Plots

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 21 rows containing non-finite values (stat_smooth).

## Warning: Removed 21 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 110 rows containing non-finite values (stat_smooth).
## Warning: Removed 110 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 110 rows containing non-finite values (stat_smooth).

## Warning: Removed 110 rows containing missing values (geom_point).

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 110 rows containing non-finite values (stat_smooth).

## Warning: Removed 110 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 21 rows containing non-finite values (stat_smooth).
## Warning: Removed 21 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 110 rows containing non-finite values (stat_smooth).
## Warning: Removed 110 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 110 rows containing non-finite values (stat_smooth).

## Warning: Removed 110 rows containing missing values (geom_point).

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 110 rows containing non-finite values (stat_smooth).

## Warning: Removed 110 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 110 rows containing non-finite values (stat_smooth).

## Warning: Removed 110 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 110 rows containing non-finite values (stat_smooth).

## Warning: Removed 110 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 110 rows containing non-finite values (stat_smooth).

## Warning: Removed 110 rows containing missing values (geom_point).

## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 90 rows containing non-finite values (stat_smooth).
## Warning: Removed 90 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 90 rows containing non-finite values (stat_smooth).

## Warning: Removed 90 rows containing missing values (geom_point).
## `geom_smooth()` using method = 'gam' and formula 'y ~ s(x, bs = "cs")'
## Warning: Removed 90 rows containing non-finite values (stat_smooth).

## Warning: Removed 90 rows containing missing values (geom_point).

### Anthocyanin and Chlorophyll

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Anth5
##             Df  Sum Sq Mean Sq F value    Pr(>F)    
## F1$Chl5      1 0.33366 0.33366  217.73 < 2.2e-16 ***
## Residuals 1788 2.74003 0.00153                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared
## [1] 0.1085545

Anthocyanin and Flavonol

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Anth5
##             Df  Sum Sq  Mean Sq F value    Pr(>F)    
## F1$Flav5     1 0.08082 0.080820  48.283 5.148e-12 ***
## Residuals 1788 2.99288 0.001674                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared
## [1] 0.02629407

Anothcyanin and Height 2018

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Anth5
##             Df  Sum Sq   Mean Sq F value Pr(>F)
## F1$H185      1 0.00199 0.0019900  1.1487  0.284
## Residuals 1699 2.94338 0.0017324

  • R.squared
## [1] 0.0006756401

Anthocyanin and Height 2019

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Anth5
##             Df Sum Sq    Mean Sq F value Pr(>F)
## F1$H195      1 0.0000 0.00000073   4e-04 0.9836
## Residuals 1699 2.9454 0.00173359

  • R.squared
## [1] 2.490926e-07

Anthocyanin and Height Difference Between 2018 and 2019

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Anth5
##             Df  Sum Sq   Mean Sq F value Pr(>F)
## F1$HD5       1 0.00193 0.0019302  1.1283 0.2883
## Residuals 1699 2.90657 0.0017108

  • R.squared
## [1] 0.0007111262

Chlorophyll and Flavonol

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Anth5
##             Df  Sum Sq  Mean Sq F value    Pr(>F)    
## F1$Flav5     1 0.08082 0.080820  48.283 5.148e-12 ***
## Residuals 1788 2.99288 0.001674                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared
## [1] 0.02629407

Chlorophyll and Height 2018

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Chl5
##             Df Sum Sq Mean Sq F value Pr(>F)
## F1$H185      1    414  413.56  1.9052 0.1677
## Residuals 1699 368794  217.07

  • R.squared
## [1] 0.001120119

Chlorophyll and Height 2019

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Chl5
##             Df Sum Sq Mean Sq F value Pr(>F)
## F1$H195      1     78  78.221    0.36 0.5486
## Residuals 1699 369130 217.263

  • R.squared
## [1] 0.0002118618

Chlorophyll and Height Difference Between 2018 and 2019

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Chl5
##             Df Sum Sq Mean Sq F value Pr(>F)
## F1$HD5       1    197  196.57   0.901 0.3426
## Residuals 1699 370658  218.16

  • R.squared
## [1] 0.0003842085

Flavonol and Height 2018

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Flav5
##             Df Sum Sq  Mean Sq F value Pr(>F)
## F1$H185      1  0.073 0.073328  1.3145 0.2517
## Residuals 1699 94.773 0.055782

  • R.squared
## [1] 0.0007731187

Flavonol and Height 2019

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Flav5
##             Df Sum Sq  Mean Sq F value  Pr(>F)  
## F1$H195      1  0.205 0.204977  3.6797 0.05525 .
## Residuals 1699 94.642 0.055704                  
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared
## [1] 0.002161139

Flavonol and Height Difference Between 2018 and 2019

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$Flav5
##             Df Sum Sq Mean Sq F value   Pr(>F)   
## F1$HD5       1  0.584 0.58427  10.637 0.001131 **
## Residuals 1699 93.324 0.05493                    
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared
## [1] 0.006134827

Height 2018 and 2019

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$H185
##             Df Sum Sq Mean Sq F value    Pr(>F)    
## F1$H195      1 125710  125710  740.77 < 2.2e-16 ***
## Residuals 1719 291720     170                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared
## [1] 0.3011528

Height 2018 and Height Difference Between 2018 and 2019

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$H185
##             Df Sum Sq Mean Sq F value    Pr(>F)    
## F1$HD5       1  89593   89593  469.78 < 2.2e-16 ***
## Residuals 1719 327837     191                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared
## [1] 0.2148603

Height 2019 and Height Difference Between 2018 and 2019

  • ANOVA
## Analysis of Variance Table
## 
## Response: F1$H195
##             Df Sum Sq Mean Sq F value    Pr(>F)    
## F1$HD5       1 101633  101633   533.2 < 2.2e-16 ***
## Residuals 1719 327656     191                      
## ---
## Signif. codes:  0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1

  • R.squared
## [1] 0.2148603